A multitude of wireless communications systems are in common use today. Mobile telephones, pagers and wireless-connected computing devices such as personal digital assistants (PDAs) and laptop computers provide portable communications at virtually any locality. Wireless local area networks (WLANs) and wireless personal area networks (WPANs) according to the Institute of Electrical and Electronic Engineers (IEEE) specifications 802.11 (WLAM) (including 802.11a, 802.11b, 802.11g, 802.11n, etc.), 802.15.1 (WPAN) and 802.15.4 (WPAN-LR) also provide wireless interconnection of computing devices and personal communications devices, as well as other devices such as home automation devices.
Within the above-listed networks and wireless networks in general, in many commercial and industrial applications it is desirable to know the location of mobile wireless devices like RFID tags.
A typical application of such a location system includes storage of real time location information as well as other data that is transmitted by the tag such as temperature, pressure and other telemetry data.
The location server of the location system generates location reports including the estimated position of the tag, the tag identification and optionally any other information reported by the tag itself as telemetry data. Typically the location report also includes the time stamp of the time (date and time) in which the tag reports were received by the location server.
The location information would turn into business related data that has tangible context that the end user of the location application can relate to.
Tangible data context can be a location, map or a zone within the location that has name which the user is familiar with or he can relate to, a business status of an object to which the tag is attached (e.g. infusion pump, bed, car or any other kind of asset), an ID of a person carrying the tag or a category that an asset belongs to.
The total volume of location reports generated by the location server that the application would have to process is derived from a number of parameters, some of which are:                a. The number of mobile units that the system can receipt. For example those mobile units may be RFID (Radio Frequency Identification) tags or mobile devices such as a PDA.        b. The mobile unit transmission rate.        c. The total number of location reports reported by the location system.        d. The number of location systems that are connected to the location application.        
A system which analyses and stores all location reports in a naive way; where each location report containing data is stored and processed, will run, after a very short time, out of resources and the end user may be required to purchase a higher grade of a database server and purge the data more frequently.
The following is a simple RTLS (Real Time Location System) scenario that can illustrate the background for the invention:
A typical location application in a hospital which manages 5,000 assets, each asset has one RFID tag attached to it. The RFID tags transmit at an average blink rate of once every 2 minutes. This report rate relates to active RFID tags, or other active components reporting independently such as a laptop computer with a wireless network card or Passive RFID tags reporting in the in the vicinity of a passive RFID readers or gates.
The following is a calculation of the number of records in the database of the system, using the above scenario:
Number of Assets=5000.
Average blink rate=once every 2 minutes or 30 times per hour.                The number of location reports every hour that will flow into the system is: 30×5,000=150,000 records.        The number of location reports every 24 hours will be 24×150,000=3,600,000 records.        Assuming that the average history required by the application is 60 days, the number of records to be stored in the system will be 216,000,000 records.        Altering one of the parameters in the description of the example above, i.e. number of assets, average report rate or history required will have an impact on the total number of records and the system performance. For instance, adding 3,000 RFID tags or other type of mobile units and assuming all other parameters do not change, would generate 345,600,600 records that have to be stored and analyzed every 60 days.        
Thus, a need existed to provide a system and method to overcome the above problem. The current invention is addressed to significantly reduce the load and/or size of a database by reducing the amount of data stored and analyzed by the location system application.